MIT Project Oxygen A Seminar Report

Submitted to the faculty of Computer Engineering, Bharati Vidyapeeth University, Pune

Submitted By: Pranav Prakash Roll No 25 Under the guidance of Mrs. S.S. Dhotre DEPARTMENT OF COMPUTER ENGINEERING, BVU COLLEGE OF ENGINEERING, PUNE

Bharati Vidyapeeth University College of Engineering, Pune

CETIFICATE This is to certify that Pranav Prakash has carried out a seminar on MIT Project Oxygen under my guidance in partial fulfillment of the requirement for the degree of Bachelor of Technology in Computer Engineering of Bharati Vidyapeeth University, Pune during the academic year 2007-08. To the best of my knowledge and belief this work has not been submitted elsewhere for the award of any other degree.

Mrs. S.S. Dhotre (Seminar Guide)

Prof. Suhas H. Patil (Head of Computer Engineering & IT Department)

Date:: Place:: Pune, India ii

ACKNOWLEDGMENT

I would like to express my thanks towards my seminar guide Mrs S.S. Dhotre for her invaluable co-operation and guidance that she gave me throughout my seminar. I would also like to thank our, head of department Prof. S.H. Patil for inspiring me and providing me all the lab facilities with the Internet, which made this seminar work very convenient. I would also like to express my appreciation and thanks to all my friends who knowingly or unknowingly have assisted and encourage me through out my hard work. Finally how can I forget the almighty the supreme power the GOD and my loving parents without which this work task was a distant dream.

Pranav Prakash BE Comp1, Roll # 25 Dept. Of Computer Engineering Bharati Vidyapeeth University, College of Engineering

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Abstract Bringing abundant computation and communication, as pervasive and free as air, naturally into people's lives. Project Oxygen is a collaborative effort involving many research activities throughout the Laboratory for Computer Science (LCS) and the Artificial Intelligence Laboratory (AIL) at the Massachusetts Institute of Technology (MIT). The Oxygen vision is to bring an abundance of computation and communication within easy reach of humans through natural perceptual interfaces of speech and vision so computation blends into peoples’ lives enabling them to easily do tasks they want to do – collaborate, access knowledge, automate routine tasks and their environment. In other words, pervasive, human-centric computing. At first blush, this catch-phrase appears vacuous. Today, computers are certainly pervasive; it is likely, at this moment, you are within 100 meters of a computer. Computers are certainly human-centric; what else can they be? On the other hand, computers are not yet as pervasive as is electricity or water. Although computers perform jobs required by humans, they do not feel human-centric – humans must conform to an unnatural way of communicating and interacting with computers. Finally, the tasks described have little to do with computation; computer- mediated functions is a more accurate term but sounds awkward. But the fact is that computers are still not as pervasive as they should be. We do communicate with computers, but on their terms. We have to live in a world created by them, in order to communicate with them. Project oxygen aims at bring computers into the life of people, as it would become an essential part of the human society, the human civilization.

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INDEX S.No. Topic

1

2

3

Page No.

Abstract

iv

Introduction

6

1.1

Pervasive Computing

6

1.2

Human Centered Computing

7

Overview of Project Oxygen

8

2.1 Vision

8

2.2 Approach

8

2.3 Challenges

10

2.4 Applications

11

Device Technologies

13

3.1

E21 Intelligent Spaces

13

3.2

H21 Mobile Devices

15

4

Network Technologies

18

5

Software Technologies

21

6

Perpetual Technologies

23

6.1

Speech

23

6.2

Vision

25

7

User Technologies

27

8

Oxygen Today

29

9

Conclusion

30

10

References

31

5

Chapter 1 Introduction 1.1 Pervasive Computing “The trend towards an information environment in which users have access to ICTs (Information and Communication Technologies) throughout the environment. This trend is particularly associated with the growth of wireless technologies that allow users to access online information and services remotely and synchronize data between different computers.” --Scrutiny of Acts and Regulations Committee, Australia Mark Weiser coined the phrase "ubiquitous computing," during his tenure as Chief Technologist of the Xerox Palo Alto Research Center (PARC) [7]. Recognizing that the extension of processing power into everyday scenarios would necessitate understandings of social, cultural and psychological phenomena beyond its proper ambit, Weiser was influenced by many fields outside computer science, including "philosophy, phenomenology, anthropology, psychology, post-Modernism, sociology of science and feminist criticism." He was explicit about "the humanistic origins of the ‘invisible ideal in post-modernist thought'", referencing as well the ironically dystopian Philip K. Dick novel Ubik. MIT has also contributed significant research in this field, notably Hiroshi Ishii's Things That Think consortium at the Media Lab and the CSAIL effort known as Project Oxygen [6]. Other major contributors include Georgia Tech's College of Computing, NYU's Interactive Telecommunications Program, Microsoft Research, Intel Research and Equator, Ajou-University UCRi cus research center funded by UCN Project of MIC in Korea. Pervasive computing, also called as Ubiquitous Computing is the post desktop model of human computer interaction, in which, information processing has been thoroughly integrated into everyday objects and activities. As opposed to the desktop paradigm, in which a single user consciously engages a single device for a specialized purpose, someone "using" ubiquitous computing engages many computational devices and systems simultaneously, in the course of ordinary activities, and may not necessarily even be aware that they are doing so. A variety of terms like everyware, ambiance intelligence, physical computing are also used sometimes to describe pervasive computing. At their core, all of these models share a vision of small, inexpensive, robust networked processing devices, distributed at all scales throughout everyday life and generally turned to distinctly quotidian ends. For example, a domestic ubiquitous computing environment might interconnect lighting and environmental controls with personal biometric monitors woven into clothing so that illumination and heating conditions in a room might be modulated, continuously and imperceptibly. . In these scenarios, it is already obvious that contemporary human-computer interaction models, whether command-line, menu-driven, or GUI-based, will be inappropriate and inadequate to the ubiquitous case. This suggests that the "natural" interaction paradigm appropriate to a fully robust ubiquitous computing has yet to emerge - although there is also recognition in the field that in many ways we are already living in a ubicomp world. Contemporary devices that lend some support to this latter idea include mobile phone, digital audio players, radio frequency identification tags and interactive- white boards. 6

1.2 Human Centered Computing Human-centered computing (HCC) is an emerging, interdisciplinary academic field broadly concerned with computing and computational artifacts as they relate to the human condition. Researchers and practitioners who affiliate themselves with human-centered computing usually come from one or more of the following traditional disciplines: computer science, sociology, psychology, cognitive science, anthropology, science and technology studies, and industrial design. Research in human-centered computing has multiple goals. Some researchers focus on understanding humans, both as individuals and in social groups, by focusing on the ways that human beings adopt, adapt, and organize their lives around computational technologies. Others focus on developing new design strategies for computational artifacts. Human-centered design of computational tools attempts to address problems that traditional design approaches, such as heuristic evaluations and measurements of productivity and efficiency, do not generally address. Designing computational tools for spirituality, for fun, and for leisure are some examples of non-traditional design problems that are of interest to HCC researchers and engineers. HCC researchers also bring a diverse array of conceptual and research tools to traditional computing areas such as computer-supported cooperative work, computer-supported collaborative learning, and ubiquitous computing. Human-centered computing is closely related to other interdisciplinary fields such as human-computer interaction and information science, and exactly where the boundaries between these fields lie is not clear. Broadly speaking, however, human-centered computing usually concerns itself with systems and practices of technology use. Human-computer interaction is more focused on ergonomics and the usability of computing artifacts, while information science is focused on practices surrounding the collection, manipulation, and use of information.

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Chapter 2 Overview of Project Oxygen 2.1 Vision For over forty years, computation has centered about machines, not people. We have catered to expensive computers, pampering them in air-conditioned rooms or carrying them around with us. Purporting to serve us, they have actually forced us to serve them. They have been difficult to use. They have required us to interact with them on their terms, speaking their languages and manipulating their keyboards or mice. They have not been aware of our needs or even of whether we were in the room with them. Virtual reality only makes matters worse: with it, we do not simply serve computers, but also live in a reality they create. In the future, computation will be human-centered. It will be freely available everywhere, like batteries and power sockets, or oxygen in the air we breathe. It will enter the human world, handling our goals and needs and helping us to do more while doing less. We will not need to carry our own devices around with us. Instead, configurable generic devices, either hand held or embedded in the environment, will bring computation to us, whenever we need it and wherever we might be. As we interact with these "anonymous" devices, they will adopt our information personalities. They will respect our desires for privacy and security. We won't have to type, click, or learn new computer jargon. Instead, we'll communicate naturally, using speech and gestures that describe our intent , and leave it to the computer to carry out our will. New systems will boost our productivity. They will help us automate repetitive human tasks, control a wealth of physical devices in the environment, find the information we need (when we need it, without forcing our eyes to examine thousands of search-engine hits), and enable us to work together with other people through space and time.

2.2 Approach Oxygen enables pervasive, human-centered computing through a combination of specific user and system technologies. Oxygen's user technologies directly address human needs. Speech and vision technologies enable us to communicate with Oxygen as if we're interacting with another person, saving much time and effort. Automation, individualized knowledge access, and collaboration technologies help us perform a wide variety of tasks that we want to do in the ways we like to do them [3]. Oxygen's device, network, and software technologies dramatically extend our range by delivering user technologies to us at home, at work or on the go. Computational devices, called Enviro21s (E21s), embedded in our homes, offices, and cars sense and affect our immediate environment. Handheld devices, called Handy21s (H21s), empower us to communicate and compute no matter where we are. Dynamic, self-configuring networks (N21s) help our machines locate each other as well as the people, services, and resources we want to reach. 8

Oxygen device technologies Devices in Oxygen supply power for computation, communication, and perception in much the same way that batteries and wall outlets supply power for electrical appliances. Both mobile and stationary devices are universal communication and computation appliances. They are also anonymous: they do not store configurations that are customized to any particular user. As for batteries and power outlets, the primary difference between them lies in the amount of energy they supply. Collections of embedded devices, called E21s, create intelligent spaces inside offices, buildings, homes, and vehicles. E21s provide large amounts of embedded computation, as well as interfaces to camera and microphone arrays, large area displays, and other devices. Users communicate naturally in the spaces created by the E21s, using speech and vision, without being aware of any particular point of interaction. Handheld devices, called H21s, provide mobile access points for users both within and without the intelligent spaces controlled by E21s. H21s accept speech and visual input, and they can reconfigure themselves to support multiple communication protocols or to perform a wide variety of useful functions (e.g., to serve as cellular phones, beepers, radios, televisions, geographical positioning systems, cameras, or personal digital assistants). H21s can conserve power by offloading communication and computation onto nearby E21s. Initial prototypes for the Oxygen device technologies are based on commodity hardware. Eventually, the device technologies will use Raw computational fabrics to increase performance for streaming computations and to make more efficient use of power. Oxygen network technologies Networks, called N21s, connect dynamically changing configurations of selfidentifying mobile and stationary devices to form collaborative regions. N21s support multiple communication protocols for low-power point-to-point, building-wide, and campus-wide communication. N21s also provide completely decentralized mechanisms for naming, location and resource discovery, and secure information access. Oxygen software technologies The Oxygen software environment is built to support change, which is inevitable if Oxygen is to provide a system that is adaptable, let alone eternal. Change is occasioned by anonymous devices customizing to users, by explicit user requests, by the needs of applications and their components, by current operating conditions, by the availability of new software and upgrades, by failures, or by any number of other causes. Oxygen's software architecture relies on control and planning abstractions that provide mechanisms for change, on specifications that support putting these mechanisms to use, and on persistent object stores with transactional semantics to provide operational support for change.

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Oxygen perceptual technologies Speech and vision, rather than keyboards and mice, provide the main modes of interaction in Oxygen. Multi modal integration increases the effectiveness of these perceptual technologies, for example, by using vision to augment speech understanding by recognizing facial expressions, lip movement, and gaze. Perceptual technologies are part of the core of Oxygen, not just afterthoughts or interfaces to separate applications. Oxygen applications can tailor "lite" versions of these technologies quickly to make human-machine interaction easy and natural. Graceful inter domain context switching supports seamless integration of applications. Oxygen user technologies Several user technologies harness Oxygen's massive computational, communication, and perceptual resources. They both exploit the capacity of Oxygen's system technologies for change in support of users, and they help provide Oxygen's system technologies with that capacity. Oxygen user technologies include: •

Automation technologies, which offer natural, easy-to-use, customizable, and adaptive mechanisms for automating and tuning repetitive information and control tasks. For example, they allow users to create scripts that control devices such as doors or heating systems according to their tastes.



Collaboration technologies, which enable the formation of spontaneous collaborative regions that accommodate the needs of highly mobile people and computations. They also provide support for recording and archiving speech and video fragments from meetings, and for linking these fragments to issues, summaries, keywords, and annotations.



Knowledge access technologies, which offer greatly improved access to information, customized to the needs of people, applications, and software systems. They allow users to access their own knowledge bases, the knowledge bases of friends and associates, and those on the web. They facilitate this access through semantic connection nets.

2.3 Challenges To support highly dynamic and varied human activities, the Oxygen system must master many technical challenges. It must be • • • •

pervasive—it must be everywhere, with every portal reaching into the same information base; embedded—it must live in our world, sensing and affecting it; nomadic—it must allow users and computations to move around freely, according to their needs; adaptable—it must provide flexibility and spontaneity, in response to changes in user requirements and operating conditions; 10



• •

powerful, yet efficient—it must free itself from constraints imposed by bounded hardware resources, addressing instead system constraints imposed by user demands and available power or communication bandwidth; intentional—it must enable people to name services and software objects by intent, for example, "the nearest printer," as opposed to by address; eternal—it must never shut down or reboot; components may come and go in response to demand, errors, and upgrades, but Oxygen as a whole must be available all the time.

2.4 Applications The following scenarios illustrate how Oxygen's integrated technologies make it easier for people to do more by doing less, wherever they may be. Business conference Hélène calls Ralph in New York from their company's home office in Paris. Ralph's E21, connected to his phone, recognizes Hélène's telephone number; it answers in her native French, reports that Ralph is away on vacation, and asks if her call is urgent. The E21's multilingual speech and automation systems, which Ralph has scripted to handle urgent calls from people such as Hélène, recognize the word "décisif" in Hélène's reply and transfer the call to Ralph's H21 in his hotel. When Ralph speaks with Hélène, he decides to bring George, now at home in London, into the conversation All three decide to meet next week in Paris. Conversing with their E21s, they ask their automated calendars to compare their schedules and check the availability of flights from New York and London to Paris. Next Tuesday at 11am looks good. All three say "OK," and their automation systems make the necessary reservations. Ralph and George arrive at Paris headquarters. At the front desk, they pick up H21s, which recognize their faces and connect to their E21s in New York and London. Ralph asks his H21 where they can find Hélène. It tells them she's across the street, and it provides an indoor/outdoor navigation system to guide them to her. George asks his H21 for "last week's technical drawings," which he forgot to bring. The H21 finds and fetches the drawings just as they meet Hélène. Guardian Angel Jane and her husband Tom live in suburban Boston and cherish their independence. As they have advanced in age, they have acquired a growing number of devices and appliances, which they have connected to their E21. They no longer miss calls or visitors because they cannot get to the telephone or door in time; microphones and speakers in the walls enable them to answer either at any time. Sensors and actuators in the bathroom make sure that the bathtub does not overflow and that the water temperature is neither too hot nor too cold. Their automated knowledge system keeps track of which television programs they have enjoyed and alerts them when similar programs will be shown. Just before their children moved away from the area, Jane and Tom enhanced their H21 to provide them with more help. 11

Tom uses the system now to jog his memory by asking simple questions, such as "Did I take my medicine today?" or "Where did I put my glasses?" The E21's vision system, using cameras in the walls, recognizes and records patterns in Tom's motion. When Tom visits his doctor, he can bring along the vision system's records to see if there are changes in his gait that might indicate the onset of medical problems. Jane and Tom can also set up the vision system to contact medical personnel in case one of them falls down when alone. By delivering these ongoing services, the E21 affords peace of mind to both parents and children.

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Chapter 3 Device Technologies 3.1 E21 Intelligent Spaces Vision Space-centered computation embedded in ordinary environments defines intelligent spaces populated by cameras, microphones, displays, sound output systems, radar systems, wireless networks, and controls for physical entities such as curtains, lighting, door locks, soda dispensers, toll gates, and automobiles. People interact in intelligent spaces naturally, using speech, gesture, drawing, and movement, without necessarily being aware that computation is present. Human-centered computation supports social interaction in its familiar context. People communicate with computation easily, as they do with each other, using shared knowledge and intelligence. Freely-available computation makes it easy for people to monitor and control their environment. Physical objects become immensely more useful and usable, and people and agents in other environments become immensely easier to reach. Approach Environmental devices, together called an E21, provide a local-area computational and communication back-plane for an intelligent space. E21s are connected to nearby sensors, actuators, and appliances, suitably encapsulated in physical objects. They communicate with each other and with nearby handheld devices (H21s) through dynamically configured networks (N21s). E21s provide sufficient computational power throughout the environment • • •

to communicate with people using natural perceptual resources, such as speech and vision, to support Oxygen's user technologies wherever people may be, and to monitor and control their environment.

E21s, as well as H21s, are universal communication and computation appliances. E21s leverage the same hardware components as the H21s so that the same software can run on both devices. E21s differ from H21s mainly in • • •

their connections to the physical world, the computational power they provide, and the policies adopted by the software that runs on the devices.

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Connections to the physical world E21s connect directly to a greater number and wider variety of sensors, actuators, and appliances than do H21s. These connections enable applications built with Oxygen's perceptual and user technologies to monitor and control the environment. An E21 might control an array of microphones, which Oxygen's perceptual resources use to improve communication with speakers by filtering out background noise. Similarly, it might control an array of antennas to permit improved communication with nearby H21s that, as a result of a better signal-to-noise ratio, use less power. Multiple antennas mounted on the roof of a building, as well as incoming terrestrial lines, connect through E21s to highbandwidth, local-area N21 networks. Through the N21 network, an E21 can connect unobtrusively to H21s in the hands or pockets of people in an intelligent space. It can display information on an H21 display in a person's hand or on a nearby wall-mounted display; it may even suggest that the person step a few feet down the hall. Computational power E21s provide more computational power than H21s, because they are limited neither by size and weight constraint imposed by portability nor by batteries as a source of power. Initial prototypes are based on commodity workstations. Later prototypes will use Raw computational fabrics to provide better cost-performance. This computational power provides an E21 with more powerful perceptual resources than an H21. For example, an E21 may steer an array of microphones to pick up a speaker's voice, use video imaging of lip movements to improve its speech recognition, or take into account an image-based understanding of a person's gaze, expression, and intent. Its computational power enables effective integration of multimodal perceptual resources. E21s can be viewed as massive computational sheets, embedded in the walls of buildings, that provide large amounts of aggregate computational power throughout the environment. Nearby H21s can use this power to offload work. An E21 can use its computational power to track people in an intelligent space, to recognize faces, and to provide the most convenient service it can to each person in the space. Software policies E21 software is robust. It recovers from failures by trying tasks again, trying them with a different selection of resources, or trying different plans. E21s provide software repositories, from which H21s can download code to reconfigure themselves for particular tasks. E21s provide nearby H21s with additional high-bandwidth connectivity to satellite and terrestrial networks.

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3.2 H21 Mobile Devices Vision Person-centered devices provide universal personal appliances that are inexpensive and can be carried and used anywhere. They are equipped with perceptual transducers such as a microphone, speaker, video camera, and display. In response to speech commands, they can reconfigure themselves through software into many useful appliances such as a two-way radios, cell phones, geographical positioning systems, and personal digital assistants, thereby replacing the many dedicated devices we usually carry with us, reducing overall weight, and conserving power. Approach Handheld devices, called H21s, provide flexibility in a lightweight design. They are anonymous devices that do not carry a large amount of permanent local state. Instead, they configure themselves through software to be used in a wide range of environments for a wide variety of purposes. For example, when a user picks up an anonymous H21, the H21 will customize itself to the user's preferred configuration. The H21s contain board-level antennas that enable them to couple with a wireless N21 network, embedded E21 devices, or nearby H21s to form collaborative regions.

Fig: Internal part identification of a H21 [6]

H21s, like E21s, are universal communication and computation appliances. They leverage the same hardware components as the E21s so that the same software can run on both devices. H21s differ from E21s mainly in • • •

their connections to the physical world, the computational power they provide, and the policies adopted by the software that runs on the devices. 15

Connections to the physical world Because handheld devices must be small, lightweight, and power efficient, H21s come equipped with only a few perceptual and communication transducers, plus a low-power network to extend the I/O devices to which it can connect. In particular, H21s are not equipped with keyboards and large displays, although they may be connected to such devices. Through the N21 network, an H21 can connect unobtrusively to nearby, more powerful E21s, which provide additional connections to the physical world. The H21 contains multiple antennas for multiple communications protocols that depend on the transmission range, for example, building-wide, campus wide, or point-to-point. Computational power H21s provide less computational power than E21s, because they are smaller and use batteries as a source of power. Initial prototypes are based on StrongArm processors. Later prototypes will use stream-efficient Raw microprocessors to provide better performance and to make more efficient use of power. Software policies Software enables an H21 to be a power efficient, universal personal appliance. Software provides functionality often provided by dedicated hardware (e.g., for the signal processing used in wireless communication), thereby increasing flexibility. H21s maximize performance and minimize power consumption through software (and, later, through Raw's software-reconfigurability) that adapts to current operating conditions. Software on the H21 determines the device's current location and orientation, discovers the extant communication protocols within the environment, and locates and downloads the appropriate communication and signal processing software (e.g., for AMPS or CDMA), when necessary, from other nearby H21s or E21s. Likewise, when a user asks an H21 to become a radio or television, bootstrapping software on the H21 locates and downloads the appropriate communication and signal processing software. An H21 uses local or downloaded software to reconfigure itself into particular communication devices (e.g., cell phones or radios). It receives input from its antenna, processes the input in software (or in software-configured hardware), and outputs sound from its speakers. Apart from a broadband A/D converter attached to an antenna, all signal processing takes place entirely in software, thereby minimizing the need for special-purpose DSP or ASIC hardware. H21s also serve as dynamically adaptable universal network interfaces: download-and-play coding and modulation modules enable them to incorporate new protocols and transmission methods on the fly. Adaptation enables smooth vertical hand-offs to different communication protocols, not just horizontal hand-offs to different transmitters using the same protocol. Software allows high-level protocols to adapt flexibly to changing channel conditions, as well as to changing application demands. When a transmitter notices low noise on a channel (for example, when it receives few requests for retransmission), software may reduce transmission power to conserve energy, or it may negotiate a change in modulation techniques (e.g., to use a larger constellation size) to increase the transmission bit-rate. 16

When a receiver experiences high noise on a channel, software may choose to increase the number of filter taps and clean up the signal, to drop data that won't be missed (e.g., a millisecond of voice data), to request transmission of the corrupted data, or to request a change in transmission power or modulation format. Software helps conserve power in other ways by trading off computation and communication among portable and high-power stationary devices. H21s can off-load expensive computations on nearby E21s. Similarly, since transmission power varies with distance, H21s can relay wireless transmissions through nearby E21s, thereby shifting energy consumption from battery-powered to wired devices.

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Chapter 4 Network Technologies Vision Networks make it easy to establish ad hoc collaborating communities of people and computing devices. They configure and reconfigure themselves automatically, as nodes appear, migrate, and disappear. This makes them easier to maintain than before, when networks were tuned largely for static wired topologies. Local networks connect seamlessly with each other, with satellite and terrestrial networks, and with a large number and variety of physical devices that can be used to monitor and control the physical world. Networks make it easy to locate resources, both nearby and further away, using names that express what is needed (e.g., "the nearest available printer"), rather than where to find it (e.g., myprinter.mynet.com). This makes them more useful and more resilient to failures, load conditions, and resource mobility. Networks route heterogeneous traffic efficiently, in response to application demands, through nodes that differ in connectivity, computational power, and resources. They adapt to current channel conditions, no longer treating all channels as "leaky pipes" with fixed and known diameters (peak bandwidths) and loss characteristics. This adaptability is essential for wireless channels, whose peak bandwidth and error characteristics can vary dynamically and unpredictably. RF channels, for example, are affected by terrain, weather, and interference from other transmitters. Networks respond flexibly to such unpredictability. Instead of sending all packets at low data rates or broadcasting at high power, they allow applications to trade data rates off against energy consumption. Instead of always using complex and costly error correction, they use only as much as applications require. Instead of being designed to handle unlikely combinations of worst-case conditions, they are designed more economically to handle current or common conditions. Approach Flexible, decentralized networks, called N21s, connect dynamically changing configurations of self-identifying mobile and stationary devices. N21s integrate different wireless, terrestrial, and satellite networks into one seamless Internet. Through algorithms, protocols, and middleware, they • • • •

configure collaborative regions automatically, creating topologies and adapting them to mobility and change, provide automatic resource and location discovery, without manual configuration and administration, provide secure, authenticated, and private access to networked resources, and adapt to changing network conditions, including congestion, wireless errors, latency variations, and heterogeneous traffic (e.g., audio, video, and data), by balancing bandwidth, latency, energy consumption, and application requirements.

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Collaborative regions Collaborative regions are self-organizing collections of computers and/or devices that share some degree of trust. Computers and devices may belong to several regions at the same time. Membership is dynamic: mobile devices may enter and leave different regions as they move around. Collaborative regions employ different protocols for intra-space and inter-space communication because of the need to maintain trust. Resource and location discovery N21 networks enable applications to use intentional names, not just location-based names, to describe the information and functionality they are looking for. Intentional names support resource discovery by providing access to entities that cannot be named statically, such as a full soda machine or to the surveillance cameras that have recently detected suspicious activity. N21 networks integrate name resolution and routing. Intra-space routing protocols perform resolution and forwarding based on queries that express the characteristics of the desired data or resources in a collaborative region. Late binding between names and addresses (i.e., at delivery time) supports mobility and multicast. Early binding supports high bandwidth streams and anycast. Wide-area routing uses a scalable resolver architecture; techniques for soft state and caching provide scalability and fault tolerance. N21 networks support location discovery through proximity to named physical objects (for example, low-power RF beacons embedded in the walls of buildings). Location discovery enables mobile devices to access and present location-specific information. For example, an H21 might help visitors navigate to their destination with spoken right-left instructions; held up next to a paper or an electronic poster of an old talk, it could provide access to stored audio and video fragments of the talk; pointed to a door, it could provide information about what is happening behind the door. Security A collaborative region is a set of devices that have been instructed by their owners to trust each other to a specified degree. A collaborative region that defines a meeting, for example, has a set of trust and authorization rules that specify what happens during a meeting (how working materials and presentation illustrations are shared, who can print on the local printer). Typically, trust rules for a meeting do not allow participants to write arbitrary information anywhere in the region. However, once users know what the trust rules are, they can introduce their devices into the meeting's collaborative region, with confidence that only the expected range of actions will happen, even if the details of the interactions are left to automatic configuration. Resource and location discovery systems address privacy issues by giving resources and users control over how much to reveal. Rather than tracking the identity, location, and characteristics of all resources and users at all times, these systems accept and propagate only the information that resources and users choose to advertise. Self-certifying names enable clients of discovery systems to trust the advertised information. 19

Adaptation N21 networks allow devices to use multiple communication protocols. Vertical handoffs among these protocols allow H21 devices to provide seamless and power efficient connectivity across a wide range of domains, for example, building-wide, campus wide, and point-to-point. They also enable applications to adapt to changes in channel conditions (e.g., congestion and packet loss) and in their own requirements (e.g., for bandwidth, latency, or reliability). They provide interfaces to monitoring mechanisms, which allow end-host transport agents to learn about congestion or about packet losses caused by wireless channel errors. This enables end-to-end resource management based on a unified congestion manager, which provides different flows with "shared state learning" and allows applications to adapt to congestion in ways that accommodate the heterogeneous nature of streams. Unlike the standard TCP protocol, which is tuned for bulk data transfers, the congestion manager efficiently handles congestion due to audio, video, and other real-time streaming applications, as well as to multiple short connections. N21 networks provide interfaces to control mechanisms, which enable applications to influence the way their packets are routed.

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Chapter 5 Software Technologies Vision Software systems adapt—to users, to the environment, to change, to failure—with minimal user intervention and without interruption to the services they provide. Computations follow (or appear to follow) users as they move about freely. Perceptual interfaces and knowledge access systems adapt to their user's idiosyncrasies. Networks adapt to changing configurations of participating devices. Devices adapt communication protocols to those of nearby devices, to user and application requirements, and to environmental conditions. Software systems themselves adapt when things go wrong, diagnosing and responding to problems by taking an alternative approach, rolling back to a consistent state, or taking another corrective action. Conversely, software systems are adaptable. They can be customized easily to meet individual user needs and to take advantage of newly published software. They accommodate requests for upgrades and repairs, whether user-supplied or system-generated, to • • • •

bring applications just-in-time to handheld devices, automatically install and upgrade software on personal machines, maintain databases (e.g., for computer-aided design systems) across software upgrades, or update networks of distributed embedded devices that lack individual user interfaces.

Approach Project Oxygen's software architecture provides mechanisms for • • • • •

building applications using composable, distributed components, customizing, adapting, and altering component behavior, replacing components, at different degrees of granularity, in a consistent fashion, person-centric, rather than device-centric, security, and disconnected operation and nomadic code.

Oxygen's software architecture relies heavily on abstraction to support change through adaptation and customization, on specification to support components that use these abstractions, and on persistent object stores with transactional semantics to provide operational support for change. Abstraction Computations are modular, as is storage. Abstractions characterize components that carry out computations and objects used in computations. In Oxygen, abstractions support the use of adaptable components and objects by providing •

application access to components traditionally hidden beneath intervening layers of software, so as to observe and influence their behavior, 21

• •





intent-based interfaces, not just syntax or address-based interfaces, so as to facilitate component and object use, adjustment, replacement, and upgrade, stream-oriented interfaces that treat speech, vision, and sensor data as first-class objects, so as to enable compilers to manage low-level pipelining concurrency and multi threaded programs to adjust their behavior correctly at runtime in response to changes in the number of streams or the interactions among them, constraint and event abstractions, which separate computation from control, trigger what is processed when, and provide flexibility for modifying behavior at runtime without compromising system integrity, cutpoints, so as to provide safe fallbacks and to enable “eternal computation".

Specifications Specifications make abstractions explicit, exposing features to other system components. In Oxygen, specifications support adaptation and change by providing information about • • • • •

system configurations, to determine what modules and capabilities are available locally, module repositories, to provide code over the network for installation on handheld and other devices, module dependencies, to support complete and consistent installations or upgrades, module capabilities, to support other components and applications in scripting their use, and module behavior, to support their safe use through a combination of static and runtime checks.

Persistent object store with transactional semantics Code, data objects, and specifications reside in a common object-oriented store, which supports all Oxygen technologies (i.e., user, perceptual, system, and device technologies). Object-orientation helps maintain the integrity of the store by restricting updates to those performed by methods in the store. The store has transactional semantics, which enables concurrent access, rollback and recovery, and consistent updates to modules and data [2]. It also operates efficiently, using techniques such as optimistic concurrency, pre-fetching, and lazy updates and garbage collection, which defer the costs of modifying the store as long as possible or until there is time to spare.

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Chapter 6 Perpetual Techniques 6.1 Speech Interaction Vision Humans communicate with computers, in much the same way they communicate with one another, using speech to create, access, and manage information and to solve problems. They ask for documents and information (e.g., "Show me John's home page" or "Will it rain tomorrow in Seattle"), without having to know where and how the information is stored, that is, without having to remember a URL, search through the Web for a pointer to a document, or use keyword search engines. They specify natural constraints on the information they want (e.g., "I want to fly from Boston to Hong Kong with a stopover in Tokyo" or "Find me a hotel in Boston with a pool and a Jacuzzi"), without having to step through fixed sets of choices offered by rigid, preconceived indexing and command hierarchies [5]. Users and machines engage in spontaneous, interactive conversations, arriving incrementally at the desired information in a small number of steps. Neither requires substantial training, a highly restricted vocabulary, unnatural pauses between words, or ideal acoustic conditions. By shifting the paradigm of interacting with computation to a perceptual one, spoken language understanding frees the user's limited cognitive capacities to deal with other more interesting and pressing matters. Approach The spoken language subsystem provides a number of limited-domain interfaces, as well as mechanisms for users to navigate effortlessly from one domain to another. Thus, for example, a user can inquire about flights and hotel information when planning a trip, then switch seamlessly to obtaining weather and tourist information. The spoken language subsystem stitches together a set of useful domains, thereby providing a virtual, broad-domain quilt that satisfies the needs of many users most of the time. Although the system can interact with users in real-time, users can also delegate tasks for the system to perform offline. The spoken language subsystem is an integral part of Oxygen's infrastructure, not just a set of applications or external interfaces. Four components, with well-defined interfaces, interact with each other and with Oxygen's device, network, and knowledge access technologies to provide real-time conversational capabilities.

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Fig: A schematic diagram showing speech interaction

Speech recognition The speech recognition component converts the user's speech into a sentence of distinct words, by matching acoustic signals against a library of phonemes—irreducible units of sound that make up a word. The component delivers a ranked list of candidate sentences, either to the language-understanding component or directly to an application. This component uses acoustic processing (e.g., embedded microphone arrays), visual clues, and application-supplied vocabularies to improve its performance. Language understanding The language understanding-component breaks down recognized sequences of words grammatically, and it systematically represents their meaning. The component is easy to customize, thereby easing integration into applications. It generates limited-domain vocabularies and grammars from application-supplied examples, and it uses these vocabularies and grammars to transform spoken input into a stream of commands for delivery to the application. It also improves language understanding by listening throughout a conversation— not just to explicit commands—and remembering what has been said [4]. Language generation The language generation component builds sentences that present application-generated data in the user's preferred language. Speech synthesis A commercial speech synthesizer converts sentences, obtained either from the language generation component or directly from the application, into speech. 24

6.2 Visual Interaction Vision Humans interact with computers, much as they interact with one another, using multiple perceptual modalities to communicate their wishes easily and intuitively. They say "show it to me there," turning their heads or pointing with their arms to indicate where. They point a handheld device at a scene or an object, and ask the computer to find visually similar images and to provide information related to those images. Humans communicate with computers implicitly, using facial expressions and gestures, without having to express everything in words. Computers recognize and classify features (e.g., faces and automobiles) and actions (e.g., gestures, gait, and collisions) in their field of vision. They detect patterns and object interactions (e.g., people entering a room or traffic accidents). They use this knowledge to retrieve distributed information, and they generate images that convey information easily and intuitively to users. For example, they show how a scene would look if viewed from different vantage points, illuminated differently, or changed by some event (e.g., aging or the arrival or disappearance of some object). Approach The visual processing system contains visual perception and visual rendering subsystems. The visual perception subsystem recognizes and classifies objects and actions in still and video images. It augments the spoken language subsystem, for example, by tracking direction of gaze of participants to determine what or whom they are looking at during a conversation, thereby improving the overall quality of user interaction. The visual rendering subsystem enables scenes and actions to be reconstructed in three dimensions from a small number of sample images without an intermediate 3D model. It can be used to provide macroscopic views of application-supplied data. Like the spoken language subsystem, the visual subsystem is an integral part of Oxygen's infrastructure. Its components have well-defined interfaces, which enable them to interact with each other and with Oxygen's device, network, and knowledge access technologies. Like lite speech systems, lite vision systems provide user-defined visual recognition, for example, of faces and handwritings. Object recognition A trainable object recognition component automatically learns to detect limited-domain objects (e.g., people or different kinds of vehicles) in unconstrained scenes using a supervised learning technology. This learning technology generates domain models from as little information as one or two sample images, either supplied by applications or acquired without calibration during operation. The component recognizes objects even if they are new to the system or move freely in an arbitrary setting against an arbitrary background.

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As people do, it adapts to objects, their physical characteristics, and their actions, thereby learning to improve object-specific performance over time. For high-security transactions, where face recognition is not a reliable solution, a vision-based biometrics approach (e.g., fingerprint recognition) integrates sensors in handheld devices transparently with the Oxygen privacy and security environment to obtain cryptographic keys directly from biometrics measurements. Activity monitoring and classification An unobtrusive, embedded vision component observes and tracks moving objects in its field of view. It calibrates itself automatically, using tracking data obtained from an array of cameras, to learn relationships among nearby sensors, create rough site models, categorize activities in a variety of ways, and recognize unusual events.

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Chapter 7 User Technologies Vision We can access, anytime and anywhere, facts and other knowledge we deem useful in our personal and professional lives. A personalized repository organizes information that interests us, keeps track of how we access that information, and contains annotations about its relevance, quality, and comprehensibility. We access our repositories in our own way. When we want more information, we can access repositories that trusted friends and associates are willing to share. By interacting with them, we leverage not only their own information, but also their knowledge of what interests us. When we want still more information, we can access widely available knowledge, for example, in libraries or on the Web. We can ask for "the fat book on computers I skimmed last week." We will get different responses to a query about "apples" if we are computer scientists, farmers, or in the process of filling out a grocery list. We do not get the same undesirable results each time we search the Web for a particular topic. Approach The individualized knowledge access subsystem supports the natural ways people use to access information. In particular, it supports personalized, collaborative, and communal knowledge, "triangulating" among these three sources of information to find the information people need. It observes and adapts to its users, so as to better meet their needs. The subsystem integrates the following components to gather and store data, to monitor user access patterns, and to answer queries and interpret data. 1. Data representation. The subsystem stores information encountered by its users using an extensible data model that links arbitrary objects via arbitrarily named arcs. There are no restrictions on object types or names. Users and the system alike can aggregate useful information regardless of its form (text, speech, images, video). The arcs, which are also objects, represent relational (database-type) information as well as associative (hypertext-like) linkage. For example, objects and arcs in A's data model can represent B's knowledge of interest to A—and vice versa. 2. Data acquisition. The subsystem gathers as much information as possible about the information of interest to a user. It does so through raw acquisition of data objects, by analyzing the acquired information, by observing people's use of it, by encouraging direct human input, and by tuning access to the user. 3. Automatic access methods. The arrival of new data triggers automated services, which, in turn, obtain further data or trigger other services. Automatic services fetch web pages, extract text from postscript documents, identify authors and titles in a document, recognize pairs of similar documents, and create document summaries that can be displayed as a result of a query. The system allows users to script and add more services, as they are needed. 27

4. Human access methods. Since automated services can go only so far in carrying out these tasks, the system allows users to provide higher quality annotations on the information they are using, via text, speech, and other human interaction modalities. 5. Automated observers. Subsystems watch the queries that users make, the results they dwell upon, the files they edit, the mail they send and receive, the documents they read, and the information they save. The system exploits observations of query behavior by converting query results into objects that can be annotated further. New observers can be added to exploit additional opportunities. In all cases, the observations are used to tune the data representation according to usage patterns.

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Chapter 8 Oxygen Today Oxygen technologies are entering our everyday life. Here are some of the technologies tested at the MIT Labs and the Oxygen Industry partners. 1. Distribution and Mobility: The Cricket location support system provides an inner analog of GPS. The Intentional Naming System provides resource discovery based on what services do, rather than where they are located at. The Self Certifying and Cooperating File system provide secure access to data over untrusted networks without requiring centralised control [1]. 2. Perceptual interfaces. Multimodal systems enhance recognition of both speech and vision. Multilingual systems support dialogs among participants speaking different languages. The SpeechBuilder utility supports development of spoken interfaces. Person tracking, face, gaze, and gesture recognition utilities support development of visual interfaces. Systems that understand sketching on white boards provide more natural interfaces to traditional software packages. 3. Semantic content. Haystack and the Semantic Web support personalized information management and collaboration through metadata management and manipulation. ASSIST helps extract design rationales from simple sketches. 4. Security and privacy. Trusted software proxies provide secure, private, and efficient access to networked and mobile devices and people. Decentralization in Oxygen aids privacy: users can locate what they need without having to reveal their own location [7]. 5. Software and hardware architectures. MetaGlue is a robust architecture for software agents. The GOALS system integrates software services to accomplish user-defined goals. RAW and Scale expose hardware to compilers, which optimize the use of circuitry and power. StreamIt provides a language and optimizing compiler for streaming applications [6].

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Chapter 9 Conclusion Mark Weiser’s vision of ubiquitous, pervasive computing is gradually becoming reality. This is evident by the recent commercial success of portable and wearable devices, smart applications and intelligent agent technologies. Project Oxygen aims at introducing computers to the human society in an entirely different way, that has been a distant dream till now. But the pace at which the current research work is going on, this seems that very soon, we will be in an environment of pervasive computing. Where humans and computers will interact in the informal way, the way humans communicate with each other.

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Chapter 10 References Many texts have been refereed while doing work on Project Oxygen. Following is the list of them. 1. Asim Smailagic and David Kogan,Location sensing and privacy in a Context-aware computing environment, IEEE Wireless communications, October 2002 2. IEEE Pervasive Computing, Context Aware Computing [Volume: 1 Issue: 3, 2002] 3. Michel L. Dertouzos, The Future of computing, Scientific American, July 1999 4. MIT Panelists, technology partners, breathe in the heady stuff of Oxygen, MASS High Tech, July 2000 5. Thad E. Starner, Wearable Computing, The journal of Pervasive Computing, IEEE March 2003 6. The official website of MIT Project Oxygen. http://oxygen.csail.mit.edu/ 7. Weiser, Mark; Rich Gold and John Seely Brown (1999). "The origins of ubiquitous computing” research at PARC in the late 1980s"". IBM systems journal 38 (4). http://www.almaden.ibm.com/research/

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